Improving S-Curve Bias Through Joint Compensation of HPA and Filter Distortions

Navigation signals are simultaneously affected by nonlinear distortion from the high-power amplifier (HPA) and linear distortion from the filter in the navigation signal transmission channel, which reduce the signal quality and degrade the performance in high-precision positioning services. To address the limitation of traditional compensation methods under nonlinear conditions, this proposes a joint compensation approach. The approach first employs an iterative piecewise optimization method to design a predistortion filter to enhance the compensation ability for linear distortion. Then a QR-decomposition recursive least squares parameter extraction algorithm is used to extract the actual HPA model and construct a lookup table, enabling adaptive compensation of nonlinear distortion. With S-curve bias (SCB) as the performance evaluation index, the results show that this method can significantly reduce the SCB and effectively compensate for the distortion. The findings indicate that the proposed method improves navigation signal quality and provides reliable support for high-precision positioning services.

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Publication Details

Journal
Sensors
Published
2026-02-03
DOI
https://doi.org/10.3390/s26030981
Primary Topic
GNSS positioning and interference
Type
article
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article

Improving S-Curve Bias Through Joint Compensation of HPA and Filter Distortions

Tulin Xiong, Yi Yang, Longyu Chen, Lin Chen et al.
Sensors
GNSS positioning and interference
article

Improving S-Curve Bias Through Joint Compensation of HPA and Filter Distortions

Tulin Xiong, Yi Yang, Longyu Chen, Lin Chen, Yuqi Liu
article en

Abstract

Navigation signals are simultaneously affected by nonlinear distortion from the high-power amplifier (HPA) and linear distortion from the filter in the navigation signal transmission channel, which reduce the signal quality and degrade the performance in high-precision positioning services. To address the limitation of traditional compensation methods under nonlinear conditions, this proposes a joint compensation approach. The approach first employs an iterative piecewise optimization method to design a predistortion filter to enhance the compensation ability for linear distortion. Then a QR-decomposition recursive least squares parameter extraction algorithm is used to extract the actual HPA model and construct a lookup table, enabling adaptive compensation of nonlinear distortion. With S-curve bias (SCB) as the performance evaluation index, the results show that this method can significantly reduce the SCB and effectively compensate for the distortion. The findings indicate that the proposed method improves navigation signal quality and provides reliable support for high-precision positioning services.

SensorsVol. 26(3)
Openalex Percentile: Top 68%
GNSS positioning and interference
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